Win-loss analysis template: what to record on every closed deal, and the four tables it produces

Win-loss analysis has a reputation as a consultancy project. The useful version is seven fields on every closed deal and four tables once a quarter.

The seven fields

Mandatory at close. Thirty seconds per deal.

The reason list

Eight to ten, mutually exclusive, the same for wins and losses where possible.

No free-text other. If a tenth of deals need one, the list is missing a reason.

The price rule. Selecting price requires two more fields: what the customer chose, and the price they paid if known. A rep who cannot fill them in does not know the deal was lost on price.

Table 1: win rate by segment and size

Large manufacturing deals win at 12 percent against 31 percent in distribution. Either the offer does not fit large manufacturers or the team cannot reach their decision-makers; the other fields say which. The win rate by segment guide covers why one blended rate hides this.

Table 2: win rate by competitor faced

Competitor B is the problem, not competitor A. And a third of losses went to nobody, which is a qualification issue no competitive battlecard will fix.

Table 3: win rate by source

The cost of a won deal differs by a factor of five or more across these rows. This table decides where prospecting time goes.

Table 4: losses by stage reached

A third of losses at proposal, combined with decision-maker reached at 35 percent on those deals, says proposals are going to people who cannot say yes.

The decision-maker field

On most teams this is the widest gap of any field. It is also a leading indicator that can be checked on open deals today.

Interviews: a few, chosen well

Each quarter, five to eight customer conversations: the largest losses, any loss at verbal stage, a win against competitor B, a no-decision on a deal forecast as committed. Someone other than the rep asks.

1. What were you trying to solve, and what prompted it then?
2. Who was involved in deciding, and how was it decided?
3. Who else did you consider, and why them?
4. What stood out about us, good and bad?
5. What was the deciding factor?
6. If you chose someone else: what could we have done differently, and would it have mattered?
7. How did price compare, and how much did it matter?

Compare the answer to question 5 with the reason the rep recorded. The rate of agreement is itself worth tracking.

A copyable closed-deal form

Outcome: won / lost to competitor / no decision / withdrawn Primary reason: [one from list] If price: chosen alternative; price paid if known Competitor: [list] / incumbent / in-house / none Furthest stage: Value: Source: Decision-maker reached: yes / no One sentence: what would you do differently?

Where it goes wrong

Free text. Four hundred unique reasons; nothing can be counted.

Price unexamined. Sixty percent of losses, and a discounting programme that changes nothing.

Losses only. Nothing learned about what works.

Small cells read as findings. A competitor faced four times, lost three, declared a threat.

Stalled deals never closed. They never reach the form, so the largest category of loss, no decision, is missing from the data. See the pipeline review template.

The short version

Seven fields at close, a short fixed reason list, a rule that makes price earn its place, four tables a quarter with counts in every cell, and a handful of interviews to check the reps' reasons against the customers'. For the rates themselves, see what is a good win rate. Covirage computes the four tables from the opportunity export each quarter, with counts shown and thin cells greyed.